Please use this identifier to cite or link to this item:
http://223.31.159.10:8080/jspui/handle/123456789/1555
Title: | Comprehensive profiling of rRNA-derived small RNAs in Arabidopsis thaliana using rsRNAfinder pipeline |
Authors: | Kalakoti, Garima Vivek, AT Kamboj, Anshul Singh, Ajeet Chakraborty, Srija Kumar, Shailesh |
Keywords: | Arabidopsis thaliana Ribosomal RNA non-coding RNA rRNA derived small RNAs rsRNAfinder sRNA-seq |
Issue Date: | 2024 |
Publisher: | Elsevier B.V. |
Citation: | MethodsX, 12: 102494 |
Abstract: | Ribosomal RNA (rRNA) gives rise to non-random small RNA fragments known as ribosomal-derived small RNAs (rsRNAs), which despite their biological importance, have been relatively understudied in comparison to other short non-coding RNAs. There exists a compelling necessity to develop a methodology for the identification, categorization, and quantification of rsRNAs from small RNA sequencing (sRNA-seq) data sets, considering the unique characteristics of ribosomal RNA (rRNA). To bridge this gap, we introduce 'rsRNAfinder' a specialized pipeline designed within the Snakemake framework. This analytical approach enables robust identification of rsRNAs using sRNA-seq datasets from Arabidopsis thaliana. Our methodology constitutes an integrated bioinformatic pipeline designed for different kinds of analysis.1.sRNA-seq data analysis: It performs in-depth analysis of reference-aligned sRNA-seq data, facilitating rsRNA annotation and quantification.2.Parametric reporting: Our pipeline provides comprehensive reports encompassing key parameters such as rsRNA size distributions, strandedness, genomic origin, and source rRNA origin.3.Illustrative validation: We have demonstrated the utility of our approach by conducting comprehensive rsRNA annotation in Arabidopsis thaliana. This validation reveals unique rsRNAs originating from all rRNA types, each of them distinguished by distinct identity, abundance, and length. |
Description: | Accepted date: 20 November 2023 |
URI: | https://www.sciencedirect.com/science/article/pii/S2215016123004909?via%3Dihub http://223.31.159.10:8080/jspui/handle/123456789/1555 |
ISSN: | 2215-0161 |
Appears in Collections: | Institutional Publications |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
Kumar Shai_2024_1.pdf Restricted Access | 1.85 MB | Adobe PDF | View/Open Request a copy |
Items in IR@NIPGR are protected by copyright, with all rights reserved, unless otherwise indicated.